Maxime P. Look

BACKGROUND: Urokinase-type plasminogen activator (uPA) and its inhibitor (PAI-1) play essential roles in tumor invasion and metastasis. High levels of both uPA and PAI-1 are associated with poor prognosis in breast cancer patients. To confirm the prognostic value of uPA and PAI-1 in primary breast cancer, we reanalyzed individual patient data provided by members of the European Organization for Research and Treatment of Cancer-Receptor and Biomarker Group (EORTC-RBG). METHODS: The study included 18 datasets involving 8377 breast cancer patients. During follow-up (median 79 months), 35% of the patients relapsed and 27% died. Levels of uPA and PAI-1 in tumor tissue extracts were determined by different immunoassays; values were ranked within each dataset and divided by the number of patients in that dataset to produce fractional ranks that could be compared directly across datasets. Associations of ranks of uPA and PAI-1 levels with relapse-free survival (RFS) and overall survival (OS) were analyzed by Cox multivariable regression analysis stratified by dataset, including the following traditional prognostic variables: age, menopausal status, lymph node status, tumor size, histologic grade, and steroid hormone-receptor status. All P values were two-sided. RESULTS: Apart from lymph node status, high levels of uPA and PAI-1 were the strongest predictors of both poor RFS and poor OS in the analyses of all patients. Moreover, in both lymph node-positive and lymph node-negative patients, higher uPA and PAI-1 values were independently associated with poor RFS and poor OS. For (untreated) lymph node-negative patients in particular, uPA and PAI-1 included together showed strong prognostic ability (all P<.001). CONCLUSIONS: This pooled analysis of the EORTC-RBG datasets confirmed the strong and independent prognostic value of uPA and PAI-1 in primary breast cancer. For patients with lymph node-negative breast cancer, uPA and PAI-1 measurements in primary tumors may be especially useful for designing individualized treatment strategies.

The antigen levels of components of the urokinase-type plasminogen activator (uPA) system of plasminogen activation are correlated with prognosis in several types of cancers, including breast cancer. In the present study involving 2780 patients with primary invasive breast cancer, we have evaluated the prognostic importance of the four major components of the uPA system [uPA, the receptor uPAR (CD87), and the inhibitors PAI-1 and PAI-2]. The antigen levels were determined by ELISA in cytosols prepared from primary breast tumors. The levels of the four factors significantly correlated with each other; the Spearman rank correlation coefficients (r(s)) ranged from 0.32 (between PAI-2 and PAI-1 or uPAR) to 0.59 (between uPA and PAI-1). The median duration of follow-up of patients still alive was 88 months. In the multivariate analyses for relapse-free survival (RFS) and overall survival (OS), we defined a basic model including age, menopausal status, tumor size and grade, lymph node status, adjuvant therapy, and steroid hormone receptor status. uPA, uPAR, PAI-1, and PAI-2 were considered as categorical variables, each with two cut points that were established by isotonic regression analysis. Compared with tumors with low levels, those with intermediate and high levels showed a relative hazard rate (RHR) and 95% confidence interval (95% CI) of 1.22 (1.02-1.45) and 1.69 (1.39-2.05) for uPA, and 1.32 (1.14-1.54) and 2.17 (1.74-2.70) for PAI-1, respectively, in multivariate analysis for RFS in all patients. Compared with tumors with high PAI-2 levels, those with intermediate and low levels showed a poor RFS with a RHR (95% CI) of 1.30 (1.14-1.48) and 1.76 (1.38-2.24), respectively. Similar results were obtained in the multivariate analysis for OS in all patients. Furthermore, uPA and PAI-1 were independent predictive factors of a poor RFS and OS in node-negative and node-positive patients. PAI-2 also added to the multivariate models for RFS in node-negative and node-positive patients, and in the analysis for OS in node-negative patients. uPAR did not further contribute to any of the multivariate models. A prognostic score was calculated based on the estimates from the final multivariate model for RFS. Using this score, the difference between the highest and lowest 10% risk groups was 66% in the analysis for RFS at 10 years and 61% in the analysis for OS. Moreover, separate prognostic scores were calculated for node-negative and node-positive patients. In the 10% highest risk groups, the proportion of disease-free patients was only 27 +/- 6% and 9 +/- 3% at 10 years for node-negative and node-positive patients, respectively. These proportions were 86 +/- 4% and 61 +/- 6% for the corresponding 10% lowest risk groups of relapse. We conclude that several components of the uPA system are potential predictors of RFS and OS in patients with primary invasive breast cancer. Knowledge of these factors could be helpful to assess the individual risk of patients, to select various types of adjuvant treatment and to identify patients who may benefit from targeted therapies that are currently being developed.

In this study, we quantified 249 mature micro-RNA (miRNA) transcripts in estrogen receptor-positive (ER(+)) primary breast tumors of patients with lymph node-negative (LNN) disease to identify miRNAs associated with metastatic capability. In addition, the prognostic value of the candidate miRNAs was determined in ER(-)/LNN breast cancer. Unsupervised analysis in a prescreening set of 38 patients identified three subgroups predominantly driven by three miRNA signatures: an ER-driven luminal B-associated miRNA signature, a stromal miRNA signature, and an overexpressed miRNA cluster located on chromosome 19q23, but these intrinsic miRNA signatures were not associated with tumor aggressiveness. Supervised analysis in the initial subset and subsequent analysis in additional tumors significantly linked four miRNAs (miR-7, miR-128a, miR-210, and miR-516-3p) to ER(+)/LNN breast cancer aggressiveness (n = 147) and one miRNA (miR-210) to metastatic capability in ER(-)/LNN breast cancer (n = 114) and in the clinically important triple-negative subgroup (n = 69) (all P < 0.05). Bioinformatic analysis coupled miR-210 to hypoxia/VEGF signaling, miR-7 and miR-516-3p to cell cycle progression and chromosomal instability, and miR-128a to cytokine signaling. In conclusion, our work connects four miRNAs to breast cancer progression and to several distinct biological processes involved therein.